Optimal assignment of cells in PCS networks

This paper deals with the assignment problem of cells to switches in a personal communication service network. Three types of costs in a PCS network are considered in detail: the cost of handoffs, the cost of cabling, and the cost of switching. The optimal assignment problem is formulated as an integer-programming problem. A heuristic algorithm is proposed to obtain an assignment of cells in a PCS network. The proposed algorithm is compared with an existing heuristic cell assignment algorithm. By numerical examination, it is shown that the switching cost has a large effect on the solution of the cell assignment problem. The proposed algorithm obtains much better cell assignment in which the load of each switch is balanced and the total cost of a PCS network is much lower than what is obtained by the existing algorithm that does not take account of the switching cost. If the switching cost is taken into account, it has also been shown that our proposed algorithm achieves substantially the same results as the existing algorithm while requiring much less computation time.     

Optimal task scheduling algorithm for cyclic synchronous tasks in general multiprocessor networks

We develop an optimal task allocation and scheduling algorithm which minimizes the computing period for multiprocessor systems with general network structures considering task execution time and communication contentions and routing delays explicitly. We presented new ideas of scheduling: (i) individual start allowing overlapping two different iterations, (ii) the scheduling space and the scheduling graph representing feasible schedules, and (iii) the check-and-diffusion algorithm utilizing property of the start-time difference vs. the computing period. With concrete examples of scheduling spaces, segments, and schedules for various multiprocessor network architectures, we showed that individual start reduces the computing period, and our algorithm can find the optimal computing period without exhaustive search.     

CPMD-mindful task assignment for NPS-F

The multiprocessor scheduling scheme NPS-F for sporadic tasks has a high utilisation bound and an overall number of preemptions bounded at design time. NPS-F binpacks tasks offline to as many servers as needed. At runtime, the scheduler ensures that each server is mapped to at most one of the m processors, at any instant. When scheduled, servers use EDF to select which of their tasks to run. Yet, unlike the overall number of preemptions, the migrations per se are not tightly bounded. Moreover, we cannot know a priori which task a server will be currently executing at the instant when it migrates. This uncertainty complicates the estimation of cache-related preemption and migration costs (CPMD), potentially resulting in their overestimation. Therefore, to simplify the CPMD estimation, we propose an amended bin-packing scheme for NPS-F allowing us (i) to identify at design time, which task migrates at which instant and (ii) bound a priori the number of migrating tasks, while preserving the utilisation bound of NPS-F.     

多中心维修任务分配研究现状

目前战争形式发生变化,装备结构变得复杂,在作战环境多变、维修时间紧迫、维修资源有限等情况下,维修任务的合理分配显得越发重要。因此本文对多中心维修任务分配的研究现状进行了综述,总结现存的任务分配方法,以促进其进一步发展。本文首先对多中心维修任务分配问题进行了描述;然后,对基本概念进行了说明,对问题进行了分析;之后,对优先级排序、任务分配及路径规划常采用的模型与算法等进行了概述;最后,总结了当前研究的不足,并展望了未来发展的方向。     

基于多准则的动态任务分配算法的研究

针对目前任务分配算法考虑的因素往往比较固定,可扩展性和灵活性较差等缺点,提出一种基于多准则的动态任务分配算法,对任务参与者的实时情况的跟踪和分析更加精确,对任务的分配更均衡;并给出了详细的任务分配的形式化表示,各评估指标之间相互独立,增强了算法的可扩展性。另外,提出采用计时器的方法来实现推拉式结合的任务分配机制,增强了算法的灵活性,既可以按照员工对任务感兴趣程度去自主选择工作项,又可以保证系统在没有员工自主选择任务项正常运转,在不影响工作正常执行的情况下使工作流管理系统的任务分配更加人性化。     

Multi-agent-based task assignment system for virtual enterprises

Manufacturing enterprises continuously have to cope with changing markets that are unpredictable and diverse, with increased global competition and with ever-changing customer demands. These requirements have led to the emergence of the virtual enterprise (VE). The creation of these enterprises, called as VEs, is becoming a growing trend as enterprises concentrate on their core competencies and economic benefit. An enterprise participating as a member of the VE should take initiative in involvement according to the internal production condition, which is changing dynamically with independent management sovereignty. However, most of researches have not considered these issues, that is the constituting enterprises have been regarded as one of the enterprises having their work stations distributed geographically. This paper proposes a multi-agent-based task assignment system for VEs, which attempts to address the selection of individually managed partners and the process of assigning tasks to them. A case example of assigning the tasks to partners is presented to illustrate and prove the proposed system's applicability.     

A workload-dependent task assignment policy for crowdsourcing

Crowdsourcing marketplaces have emerged as an effective tool for high-speed, low-cost labeling of massive data sets. Since the labeling accuracy can greatly vary from worker to worker, we are faced with the problem of assigning labeling tasks to workers so as to maximize the accuracy associated with their answers. In this work, we study the problem of assigning workers to tasks under the assumption that workers’ reliability could change depending on their workload, as a result of, e.g., fatigue and learning. We offer empirical evidence of the existence of a workload-dependent accuracy variation among workers, and propose solution procedures for our Crowdsourced Labeling Task Assignment Problem, which we validate on both synthetic and real data sets.     

Optimal regulation of homogeneous systems

We present an offline numerical algorithm to generate a discontinuous feedback law to robustly regulate the origin of a continuous-time homogeneous system through sample and hold. The proposed feedback comes out of the solution of an infinite horizon optimization problem in discrete time and is in the form of a look-up table. We show that when applied to either chained systems or systems in power form the algorithm results in a closed loop whose origin is globally exponentially stable.     

Analysis of task assignment policies in scalable distributedweb-server systems

A distributed multiserver Web site can provide the scalability necessary to keep up with growing client demand at popular sites. Load balancing of these distributed Web-server systems, consisting of multiple, homogeneous Web servers for document retrieval and a Domain Name Server (DNS) for address resolution, opens interesting new problems. In this paper, we investigate the effects of using a more active DNS which, as an atypical centralized scheduler, applies some scheduling strategy in routing the requests to the most suitable Web server. Unlike traditional parallel/distributed systems in which a centralized scheduler has full control of the system, the DNS controls only a very small fraction of the requests reaching the multiserver Web site. This peculiarity, especially in the presence of highly skewed load, makes it very difficult to achieve acceptable load balancing and avoid overloading some Web servers. This paper adapts traditional scheduling algorithms to the DNS, proposes new policies, and examines their impact under different scenarios. Extensive simulation results show the advantage of strategies that make scheduling decisions on the basis of the domain that originates the client requests and limited server state information (e.g., whether a server is overloaded or not). An initially unexpected result is that using detailed server information, especially based on history, does not seem useful in predicting the future load and can often lead to degraded performance     

社会网络下分配众包任务的真实机制

众包平台上出现了越来越多的宏任务，而这些宏任务需要工人的专业技能和团队的集体贡献。社会网络为社会工作者之间的合作提供了一个可用的平台。事实上，很少有研究关注众包工人之间的社会网络。在社会网络下的众包任务分配问题是NP难问题，并且社会网络中会存在参与者为了提高自己的效用而谎报要价的情况，因此提出一种社会网络下分配众包任务的真实机制（TMC-SN）。在社会网络下的众包任务分配问题被模拟成一个拍卖，其中任务请求者是买家，工人是卖家，众包平台充当拍卖者。为了找出最合适的团队，TMC-SN从边际贡献和团队凝聚力两个方面来衡量工人对团队的适应性。理论分析证明，TMC-SN具有真实性、个体理性、预算平衡等经济属性。实验结果表明，TMC-SN在社会福利方面具有一定的优势，并且能够提升工人的效用。     

Harmonic analysis of homogeneous networks

We introduce a generalization of mutually inhibitory networks called homogeneous networks. Such networks have symmetric connection strength matrices that are circulant (one-dimensional case) or block circulant with circulant blocks (two-dimensional case). Fourier harmonics provide universal eigenvectors, and we apply them to several homogeneous examples: k-wta, k-cluster, on/center off/surround, and the assignment problem. We also analyze one nonhomogeneous case: the subset-sum problem. We present the results of 10000 trials on a 50-node k-cluster problem and 100 trials on a 25-node subset-sum problem.     

社会网络下分配众包任务的真实机制

众包平台上出现了越来越多的宏任务,而这些宏任务需要工人的专业技能和团队的集体贡献。社会网络为社会工作者之间的合作提供了一个可用的平台。事实上,很少有研究关注众包工人之间的社会网络。在社会网络下的众包任务分配问题是NP难问题,并且社会网络中会存在参与者为了提高自己的效用而谎报要价的情况,因此提出一种社会网络下分配众包任务的真实机制（TMC-SN）。在社会网络下的众包任务分配问题被模拟成一个拍卖,其中任务请求者是买家,工人是卖家,众包平台充当拍卖者。为了找出最合适的团队,TMC-SN从边际贡献和团队凝聚力两个方面来衡量工人对团队的适应性。理论分析证明,TMC-SN具有真实性、个体理性、预算平衡等经济属性。实验结果表明,TMC-SN在社会福利方面具有一定的优势,并且能够提升工人的效用。     

Multiagent task allocation in social networks

This paper proposes a new variant of the task allocation problem, where the agents are connected in a social network and tasks arrive at the agents distributed over the network. We show that the complexity of this problem remains NP-complete. Moreover, it is not approximable within some factor. In contrast to this, we develop an efficient greedy algorithm for this problem. Our algorithm is completely distributed, and it assumes that agents have only local knowledge about tasks and resources. We conduct a broad set of experiments to evaluate the performance and scalability of the proposed algorithm in terms of solution quality and computation time. Three different types of networks, namely small-world, random and scale-free networks, are used to represent various social relationships among agents in realistic applications. The results demonstrate that our algorithm works well and also that it scales well to large-scale applications. In addition we consider the same problem in a setting where the agents holding the resources are self-interested. For this, we show how the optimal algorithm can be used to incentivize these agents to be truthful. However, the efficient greedy algorithm cannot be used in a truthful mechanism, therefore an alternative, cluster-based algorithm is proposed and evaluated.     

A note on task assignment of several problems

In the last two decades several papers have appeared in the literature where the multi-resource generalized assignment problem (MRGAP) was used to solve different problems. In these problems the number of variables grew exponentially. The purpose of this technical note is to present an assignment model that is compact and includes the models in the previous research papers as special cases. The proposed model is a generalization of MRGAP (GMRGAP). Computational experiment with CPLEX is presented to test effectiveness of the proposed model compared to some existing ones.     

改进差分进化算法求解整数任务分配

针对0-1任务规划模型存在维数灾维的问题,提出了一种基于改进差分进化算法的整数任务分配算法。将任务分配的0-1规划模型转化整数规划模型,不仅大幅降低了优化变量的维数,还减小了整式约束条件;将差分进化算法常用的变异算子DE/rand/1/bin和DE/best/2/bin结合起来组成新的变异算子,使得DE既保持了种群的多样性,又有较快的收敛速度和搜索精度,并用改进的差分进化算法求解整数规划;通过典型的任务分配实例验证了该算法在优化大规模任务分配的有效性和快速性。     

A QoS-sensitive task assignment algorithm for mobile crowdsensing

Recently, mobile crowdsensing has attracted many researchers’ attention due to the pervasiveness of smart phones. In this paper, we study the QoS-sensitive Task Assignment (QSTA) problem for mobile crowdsensing, which involves variable tasks and flexible rewards. Each user can conduct one or more tasks, and the number of tasks assigned to each user is flexible. The reward paid to the user is related to the assigned tasks. To ensure the sensing QoS of tasks, each task might be assigned to multiple users. We prove the QSTA problem to be NP-hard, and propose a greedy algorithm to solve this problem. Moreover, we also analyze the approximation ratio of the proposed algorithm. Additionally, we demonstrate the significant performance of the algorithm through simulations     

Optimal constant due-date assignment and sequencing

This paper considers the sequencing of n jobs in a single-machine shop in which each job is assigned a constant flow allowance. The objective is to determine the optimal value of the flow allowance and the optimal job sequence to minimize a cost function based on the flow allowance and the job earliness and tardiness values. We first propose a linear programming (LP) formulation of the problem. We then derive the optimal constant flow allowance via considering the LP dual problem and show that it is independent of the job sequence. After the theoretical treatment, a numerical example is presented for discussion.